Gene network modular-based classification of microarray samples
نویسندگان
چکیده
منابع مشابه
Blind Gene Classification Based on Ica of Microarray Data
The present study shows that an ICA-based method can, e®ectively and blindly, classify a vast amount of gene expression data into biologically meaningful groups. Speci ̄cally, we show (1) that genes, whose expression data are sampled at di®erent times, can be classi ̄ed into several groups, based on the correlation of each gene with independent component curves over time, and (2) that these class...
متن کاملCollaborative representation-based classification of microarray gene expression data
Microarray technology is important to simultaneously express multiple genes over a number of time points. Multiple classifier models, such as sparse representation (SR)-based method, have been developed to classify microarray gene expression data. These methods allocate the gene data points to different clusters. In this paper, we propose a novel collaborative representation (CR)-based classifi...
متن کاملA Robust Gene Selection Method for Microarray-based Cancer Classification
Gene selection is of vital importance in molecular classification of cancer using high-dimensional gene expression data. Because of the distinct characteristics inherent to specific cancerous gene expression profiles, developing flexible and robust feature selection methods is extremely crucial. We investigated the properties of one feature selection approach proposed in our previous work, whic...
متن کاملSoFoCles: Feature filtering for microarray classification based on Gene Ontology
Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classif...
متن کاملEnsemble Dependence Model Based Cancer Classification using Gene Microarray Data
DNA microarray technologies make it possible to simultaneously monitor thousands of genes expression levels. A topic of great interest is to study the different expression profiles between microarray samples from cancer patients and normal subjects, by classifying them at gene expression level. Currently, various clustering methods have been proposed in the literature to classify cancer and nor...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2012
ISSN: 1471-2105
DOI: 10.1186/1471-2105-13-s10-s17